MUMBAI, India, July 30 -- Intellectual Property India has published a patent application (202641087385 A) filed by Madhankumar C; Dr. S. Vanitha; Dr. T. Papitha Christobel; Radhika K. Manjusha; S. Oyyathevan; Virag Shaileshkumar Shah; Arun Haydn Rundeepkumar D; Dharshini D. R; and Rajesh Kumar G on July 17, 2026, for Universal Autonomous Cognitive Engineering Intelligence Platform (uaceip): A Quantum-Neuro-Symbolic Self-Evolving Digital Twin Architecture For Cross-Domain Engineering, Scientific Research, Industrial Automation, And Sustainable Smart Infrastructure.
Inventors include Dr. S. Vanitha; Dr. T. Papitha Christobel; Radhika K. Manjusha; S. Oyyathevan; Virag Shaileshkumar Shah; Arun Haydn Rundeepkumar D; Dharshini D. R; and Rajesh Kumar G.
The application for the patent was published on July 24, 2026, under issue no. 30/2026.
Abstract: Universal Autonomous Cognitive Engineering Intelligence Platform (UACEIP): A Quantum-Neuro-Symbolic Self-Evolving Digital Twin Architecture for Cross- Domain Engineering, Scientific Research, Industrial Automation, and Sustainable Smart Infrastructure Abstract The present invention discloses a Universal Autonomous Cognitive Engineering Intelligence Platform (UACEIP) comprising a Quantum-Neuro-Symbolic Self-Evolving Digital Twin Architecture for intelligent decision-making, autonomous engineering optimization, scientific research acceleration, industrial automation, and sustainable smart infrastructure management. Conventional engineering platforms are typically domain-specific, requiring separate computational models, simulation tools, and optimization frameworks for different industries, thereby limiting interoperability, scalability, and autonomous adaptation. The proposed invention overcomes these limitations by integrating quantum- inspired computing, neuro-symbolic artificial intelligence, digital twin technology, explainable reasoning, and self-evolving learning mechanisms into a unified cognitive engineering platform capable of operating across multiple engineering and scientific domains. The system comprises a multimodal data acquisition module, quantum-inspired optimization engine, neuro-symbolic reasoning engine, digital twin simulation platform, autonomous decision-making controller, adaptive knowledge graph repository, federated learning module, cloud-edge computing infrastructure, and a continuous self-evolution engine. Real-time data from sensors, industrial equipment, IoT devices, research laboratories, enterprise systems, and environmental monitoring networks are continuously integrated into dynamic digital twins that accurately replicate physical assets, engineering processes, and scientific environments. Artificial intelligence algorithms combined with symbolic reasoning autonomously analyze system behavior, predict failures, optimize resource utilization, validate engineering constraints, and generate explainable recommendations while continuously refining computational models through self-learning. The invention further incorporates quantum-inspired optimization techniques, federated intelligence, cybersecurity mechanisms, sustainability assessment, and autonomous feedback control to enhance operational efficiency, resilience, and decision accuracy. The platform supports applications including smart manufacturing, civil infrastructure management, transportation systems, healthcare engineering, energy systems, aerospace, robotics, environmental monitoring, scientific experimentation, advanced materials research, and Industry 5.0 ecosystems. By integrating digital twins, quantum-inspired optimization, neuro symbolic reasoning, and autonomous cognitive intelligence into a unified platform, the invention significantly improves engineering productivity, scientific innovation, infrastructure sustainability, predictive maintenance, and intelligent automation, providing a scalable foundation for next-generation cross-domain engineering and research ecosystems.
Disclaimer: Curated by HT Syndication.
